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Testing for a Linear Unit Root against Nonlinear Threshold Stationarity

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Abstract

In this paper we propose a direct testing procedure to detect the presence of linear unit root against geometrically ergodic process defined by the self-exciting threshold autoregressive (SETAR) model with three regimes. Assuming that the process follows the random walk in the corridor regime, the null can be tested by the Wald test for the joint significance of the threshold autoregressive parameters under both lower and upper regimes. We prove that the suggested Wald test does not depend on unknown threshold values under the null at least asymptotically. We also derive its analytic asymptotic null distribution. Monte Carlo evidence clearly indicates that the exponential average of the Wald statistic is more powerful than the standard Dickey-Fuller test that ignores the threshold nature under the alternative.

Suggested Citation

  • George Kapetanios & Yongcheol Shin, 2000. "Testing for a Linear Unit Root against Nonlinear Threshold Stationarity," Edinburgh School of Economics Discussion Paper Series 60, Edinburgh School of Economics, University of Edinburgh.
  • Handle: RePEc:edn:esedps:60
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    File URL: http://www.econ.ed.ac.uk/papers/id60_esedps.pdf
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    Cited by:

    1. Andrew P. Blake & George Kapetanios, 2003. "Pure Significance Tests of the Unit Root Hypothesis Against Nonlinear Alternatives," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(3), pages 253-267, May.
    2. Copeland, Laurence & Heravi, Saeed, 2006. "Structural Breaks in the Real Exchange Rate Adjustment Mechanism," Cardiff Economics Working Papers E2006/21, Cardiff University, Cardiff Business School, Economics Section.

    More about this item

    Keywords

    self-exciting threshold autogressive model; exponentially ergodic process; unit roots; thresholds cointegration; Wald tests; critical values; Monte Carlo simulations;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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